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Ego-net Community Mining Applied to Friend Suggestion

Summary: Introduces a parallel method to construct and cluster every ego-net at scale, exposing high-quality local communities. Derives neighborhood-local friend-suggestion features from cross-ego-net community co-occurrence, outperforming classic similarity measures theoretically and empirically. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11512
Venue
VLDB
Year
2016
Pagerank
6.2073549e-05
Overall Rank
5,468 | 62.49%
DOI
10.14778/2850583.2850594

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{epasto_vldb16,
        title = {{Ego-net Community Mining Applied to Friend Suggestion}},
        author = {Epasto, Alessandro and Lattanzi, Silvio and Mirrokni, Vahab and Sebe, Ismail Oner and Taei, Ahmed and Verma, Sunita},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {4},
        pages = {324--335},
        doi = {10.14778/2850583.2850594},
        url = {https://doi.org/10.14778/2850583.2850594},
        year = {2016}
}

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